1 Basic details about project

1.1 Abbreviations

  • IC = intermittent claudication
  • RP = rest pain
  • TL = tissue loss
  • TASCII/TASC-II/TASC = Trans-Atlantic Inter-Society Consensus-II
  • Bal = Balloon angioplasty
  • DEB = Drug-eluting balloon
  • St = Stent
  • Sup = Supera
  • VIA = VIABAHN
  • Fail = Failed procedure
  • CFA = common femoral artery
  • P3 = P3 segment of popliteal artery
  • Lysis = intra-arterial thrombolysis
  • Tech succ = technical success
  • Complex no. = number of complexity markers

1.2 Inclusion and exclusion criteria

  • Indication criteria are:
    • Endovascular intervention to femoro-popliteal (fem-pop) segment
    • Intermittent claudication, rest pain and tissue loss
  • Exclusion criteria are:
    • Femoro-popliteal bypass graft on ipsilateral leg
    • Acute limb ischaemia or other indication not listed above
    • Previous intervention to same limb is NOT an exclusion criterion

1.3 Period covered

  • Procedures from 2016-01-11 to 2020-04-01 are included here

2 Patient information

2.1 Patients per year

  • 505 are included
  • They are spread across the years as demonstrated:

2.2 Age per year

  • Mean age of patients is 70.3 years
  • Median age of patients is 72 years
  • Age is demonstrated in this boxplot:

  • Age variation by year is demonstrated in this boxplot:

  • To check if age is evenly distributed across the years, they can be plotted to identify outliers:

  • Data points 164, 396 and 431 are outliers
  • Point 164: 37 years old (2017)
  • Point 396: 35 years old (2019)
  • Point 431: 32 years old (2019)

  • Welch’s one-way test performed instead of ANOVA due to inhomogeneity of variances, looking for a significant age difference between years:

##
##  One-way analysis of means (not assuming equal variances)
##
## data:  patients$Age and as.factor(patients$Year)
## F = 0.56858, num df = 4.00, denom df = 196.13, p-value = 0.6857

2.3 Age per indication

  • Average age by indication for intervention is as shown here:
Indication Mean age Median age
IC 64.0 65.0
RP 70.2 71.5
TL 71.9 72.0
  • These data are demonstrated in this boxplot:

  • To check if these data are evenly distributed, they can be plotted to identify outliers:

  • Data points 396, 431 and 488 are outliers
  • Point 396: 35 years old (TL)
  • Point 431: 32 years old (TL)
  • Point 164: 39 years old (RP)

  • Welch’s one-way test performed instead of ANOVA due to inhomogeneity of variances:

##
##  One-way analysis of means (not assuming equal variances)
##
## data:  patients$Age and patients$Indication
## F = 23.969, num df = 2.00, denom df = 151.89, p-value = 8.972e-10
  • Pairwise t-test with no assumption of equal variances to look for where differences in means are, given that Welch’s test was signficant:
##
##  Pairwise comparisons using t tests with non-pooled SD
##
## data:  patients$Age and patients$Indication
##
##    IC      RP
## RP 0.00057 -
## TL 3.1e-10 0.27292
##
## P value adjustment method: BH

2.4 Age per gender

  • Average age by gender for intervention is as shown here:
Gender Mean age Median age
Man 72.4 74
Woman 68.9 70
  • These data are demonstrated in this boxplot:

  • t-test test to look for differences between mean ages:
##
##  Welch Two Sample t-test
##
## data:  patients$Age by patients$Gender
## t = 3.3393, df = 378.17, p-value = 0.0009233
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  1.441131 5.568611
## sample estimates:
##   mean in group Man mean in group Woman
##            72.43367            68.92880

3 Limb information

3.1 Limbs per year

  • 551 are included
  • They are spread across the years as demonstrated:

4 Procedure information

4.1 Procedures per year

  • 622 are included
  • On average, roughly 149 procedures are performed each year
  • Or 12 per month
  • They are spread across the years as demonstrated:

4.2 TASC classification of lesions

  • These are from the 622 procedures

5 Indication information

  • Number of procedures performed for each indication are shown here:

  • Number of procedures each year for each indication are shown here:

5.1 Intermittent claudication

  • On average, roughly 25 procedures are performed each year for IC
  • Or 2.1 per month

5.1.1 By TASC

5.1.2 By TASC each year

5.2 Rest pain

## estimate only: convert to intervals for accuracy
## estimate only: convert to intervals for accuracy
  • On average, roughly 22 procedures are performed each year for RP
  • Or 1.8 per month

5.2.1 By TASC

5.2.2 By TASC each year

5.3 Tissue loss

  • On average, roughly 103.4 procedures are performed each year for TL
  • Or 8.5 per month

5.3.1 By TASC

5.3.2 By TASC each year

6 Technical success

6.1 Overall technical success

  • 91% of all fem-pop procedures are technically successful

6.2 Technical success each year

  • Kruskal-Wallis test to look for difference in success between years:
##
##  Kruskal-Wallis rank sum test
##
## data:  procedures$Successful by as.factor(procedures$Year)
## Kruskal-Wallis chi-squared = 1.0287, df = 4, p-value = 0.9054
  • Wilcoxon rank sum test to look for where differences in means are:
  • (can be ignored if p >= 0.05 for Kruskal-Wallis test)
##
##  Pairwise comparisons using Wilcoxon rank sum test
##
## data:  procedures$Success and as.factor(procedures$Year)
##
##      2016 2017 2018 2019
## 2017 0.97 -    -    -
## 2018 0.97 0.97 -    -
## 2019 0.97 0.97 0.97 -
## 2020 0.97 0.97 0.97 0.97
##
## P value adjustment method: BH

6.3 Technical success by indication

  • Kruskal-Wallis test to look for difference in success between indications:
##
##  Kruskal-Wallis rank sum test
##
## data:  procedures$Successful by procedures$Indication
## Kruskal-Wallis chi-squared = 0.010751, df = 2, p-value = 0.9946
  • Wilcoxon rank sum test to look for where differences in means are:
  • (can be ignored if p >= 0.05 for Kruskal-Wallis test)
##
##  Pairwise comparisons using Wilcoxon rank sum test
##
## data:  procedures$Success and procedures$Indication
##
##    IC   RP
## RP 0.99 -
## TL 0.99 0.99
##
## P value adjustment method: BH

6.4 Technical success by TASC-II

  • Kruskal-Wallis test to look for difference in success between indications:
##
##  Kruskal-Wallis rank sum test
##
## data:  procedures$Successful by procedures$TASCII
## Kruskal-Wallis chi-squared = 42.006, df = 3, p-value = 4.001e-09
  • Wilcoxon rank sum test to look for where differences in means are:
  • (can be ignored if p >= 0.05 for Kruskal-Wallis test)
##
##  Pairwise comparisons using Wilcoxon rank sum test
##
## data:  procedures$Success and procedures$TASCII
##
##   A       B       C
## B 0.7816  -       -
## C 0.1221  0.0313  -
## D 4.8e-06 1.6e-09 0.0063
##
## P value adjustment method: BH

7 Treatment method

7.1 All procedures

  • Overall, including failed procedures, 79% of treatments leave nothing behind

  • More specific devices:

7.2 Device by year

  • More specific devices:

7.3 Device by indication

  • The bar chart is separated into three with different y-axes to allow easy comparison of proportions

  • More specific devices:

7.4 Device by TASC-II

  • More specific devices:

8 Procedural complexity

  • Five indicators of increased procedural complexity are recorded, with a binary “yes”/“no” option being available, ie. the success of the added procedural step is not recorded:
  1. ‘Iliac’ - iliac angioplasty or stent in the same procedure
  2. ‘CFA’ - concurrent common femoral endarterectomy
  3. ‘P3’ - P3/below knee segment of the popliteal artery was treated
  4. ‘Crural’ - concurrent infra-popliteal angioplasty
  5. ‘Lysis’ - acute intra-procedural thrombus requiring intra-arterial thrombolysis

8.1 Number and percentage of individual complexity markers

Yes/No Iliac CFA P3 Crural Lysis
No 603.0 581.0 505.0 471.0 609.0
Yes 19.0 41.0 117.0 151.0 13.0
% Yes 3.1 6.6 18.8 24.3 2.1

8.2 Number of procedures with total number of complexity markers

Number of complexity markers Number Percentage
0 371 59.6
1 168 27.0
2 76 12.2
3 7 1.1

8.2.1 Procedural success by complexity

  • NB success is defined as successfully treating the fem-pop segment

  • Kruskal-Wallis test to look for difference in success between complexity levels:
##
##  Kruskal-Wallis rank sum test
##
## data:  procedures$Successful by procedures$multiComp
## Kruskal-Wallis chi-squared = 2.6244, df = 3, p-value = 0.4532
  • Wilcoxon rank sum test to look for where differences in means are:
  • (can be ignored if p >= 0.05 for Kruskal-Wallis test)
##
##  Pairwise comparisons using Wilcoxon rank sum test
##
## data:  procedures$Success and procedures$multiComp
##
##   0    1    2
## 1 0.59 -    -
## 2 0.79 0.59 -
## 3 0.59 0.59 0.59
##
## P value adjustment method: BH

9 Survival

  • Death dates were last checked 17/04/2020

  • Survival statistics are based on the 505 patients in the data
  • Kaplan-Meier survival estimator is used for survival curves
  • Log-rank test is used to sompare survival estimates between groups

9.1 Overall

  • Kaplan-Meier survival for all patients undergoing fem-pop intervention is plotted below:

9.2 By year

  • Log rank test to look for significant survival difference between groups:
##
##  Pairwise comparisons using Log-Rank test
##
## data:  patients and Year
##
##      2016 2017 2018 2019
## 2017 0.97 -    -    -
## 2018 0.97 0.95 -    -
## 2019 0.95 0.95 0.95 -
## 2020 0.95 0.95 0.95 0.95
##
## P value adjustment method: BH

9.3 By TASC-II

  • Log rank test to look for significant survival difference between groups:
##
##  Pairwise comparisons using Log-Rank test
##
## data:  patients and TASCII
##
##   A       B       C
## B 0.00159 -       -
## C 9.3e-05 0.07745 -
## D 0.00013 0.05556 0.36620
##
## P value adjustment method: BH

9.4 By Gender

  • Log rank test to look for significant survival difference between groups:
##
##  Pairwise comparisons using Log-Rank test
##
## data:  patients and Gender
##
##       Man
## Woman 0.33
##
## P value adjustment method: BH

9.5 By indication

  • Log rank test to look for significant survival difference between groups:
##
##  Pairwise comparisons using Log-Rank test
##
## data:  patients and Indication
##
##    IC      RP
## RP 5.4e-05 -
## TL 2.1e-09 0.0068
##
## P value adjustment method: BH

9.6 By technical success

  • Log rank test to look for significant survival difference between groups:
##
##  Pairwise comparisons using Log-Rank test
##
## data:  patients and Successful
##
##     No
## Yes 0.0021
##
## P value adjustment method: BH

9.7 By treatment method

  • Log rank test to look for significant survival difference between groups:
##
##  Pairwise comparisons using Log-Rank test
##
## data:  patients and Dev
##
##      Bal    St
## St   0.5940 -
## Fail 0.0054 0.0445
##
## P value adjustment method: BH

9.8 By complexity

  • Log rank test to look for significant survival difference between groups:
##
##  Pairwise comparisons using Log-Rank test
##
## data:  patients and multiComp
##
##   0    1    2
## 1 0.75 -    -
## 2 0.92 0.75 -
## 3 0.75 0.91 0.75
##
## P value adjustment method: BH

9.9 Tissue loss only

9.9.1 By TASC-II

  • Log rank test to look for significant survival difference between groups:
##
##  Pairwise comparisons using Log-Rank test
##
## data:  tlPat and TASCII
##
##   A     B     C
## B 0.151 -     -
## C 0.039 0.192 -
## D 0.039 0.192 0.600
##
## P value adjustment method: BH

9.9.2 By Gender

  • Log rank test to look for significant survival difference between groups:
##
##  Pairwise comparisons using Log-Rank test
##
## data:  tlPat and Gender
##
##       Man
## Woman 0.26
##
## P value adjustment method: BH

9.9.3 By technical success

  • Log rank test to look for significant survival difference between groups:
##
##  Pairwise comparisons using Log-Rank test
##
## data:  tlPat and Successful
##
##     No
## Yes 0.0021
##
## P value adjustment method: BH

9.9.4 By treatment method

  • Log rank test to look for significant survival difference between groups:
##
##  Pairwise comparisons using Log-Rank test
##
## data:  tlPat and Dev
##
##      Bal    St
## St   0.8884 -
## Fail 0.0064 0.0270
##
## P value adjustment method: BH

9.9.5 By complexity

  • Log rank test to look for significant survival difference between groups:
##
##  Pairwise comparisons using Log-Rank test
##
## data:  tlPat and multiComp
##
##   0    1    2
## 1 0.61 -    -
## 2 0.51 0.53 -
## 3 0.61 0.61 0.53
##
## P value adjustment method: BH

9.10 30-day survival by indication

  • Log rank test to look for significant survival difference between groups:
##
##  Pairwise comparisons using Log-Rank test
##
## data:  patients and Indication
##
##    IC    RP
## RP 1.000 -
## TL 0.086 0.086
##
## P value adjustment method: BH

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